• The Korean Journal of Applied Statistics
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• v.13 no.2
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• pp.437-445
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• 2000

The present paper is introducing a new model so called TAR-GARCH in the context of stock price analysis Conventional models such as AR(l), TAR(l), ARCH(I) and GARCH( 1,1) are briefly reviewed and TAR-GARCH is suggested in analyizing domestic stock prices. Also, relevant iterative estimation procedure is developed. It is seen that TAR-GARCH provides the better fit relative to traditional first order models for stock prices data in Korea.

• Environmental and Resource Economics Review
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• v.17 no.4
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• pp.813-843
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• 2008

This paper investigates the presence of long-run and short-run price asymmetries in weekly gasoline prices from January 1997 to July 2008. In accordance with distribution channels, wholesale and retail stages are analyzed separately. An approach based on TAR and M-TAR cointegration tests, which entail matching asymmetric ECMs, is employed. For wholesale prices, asymmetries in the links with crude oil prices and exchange rates are found for both ECMs in the long-run and short-run. Exchange rates appear to play more significant role than crude oil prices in explaining the short-run price asymmetry. The rise in crude oil prices or exchange rates has statistically significant major impact on the increase of wholesale prices on the second week, not immediately as expected in the concept of 'rockets and feathers'. And asymmetrically, the fall does not have any statistically significant effect on the same period. The finding seems to be somewhat unusual. However, for retail prices, asymmetry m connection with wholesale prices is only revealed in the long-run. A symmetric price adjustment can be assumed in the short-run. Contrary to the long-run asymmetry found in the wholesale stage, in the retail stage, the speed of adjustment for negative deviations toward long-run equilibrium is faster than for positive ones, which is a phenomenon not favorable to consumers.

• 한국방재학회:학술대회논문집
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• 2007.02a
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• pp.587-590
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• 2007

한계자기회귀모형(TAR)을 응용하여 동시에 해조와 홍수의 영향을 받을 때 삽교천 감조구간의 삽교호수위관측소의 월 최고수위를 예측하는 모형을 구축하였으며, 모형구축과정에서 유전알고리즘으로 한계값과 자기회귀계수의 매개변수를 최적화한다. 계산결과 한계자기회귀모형은 감조하천의 비선형성특성을 모의 할 수 있으며, 예측의 정확도와 예측성능의 안정성을 확보할 수 있다. 연구결과 유전한계자귀회귀모형으로 감조하천구간의 월 최고수위를 예측하는 것이 가능하며, 또한 감조하천구간에서 기타 수문요소의 비선형성 서열예측 중에서도 광범한 실용가치가 있다고 본다.

• Korea Real Estate Review
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• v.24 no.1
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• pp.7-14
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• 2014

This study, as the temporal and spatial data for the real price apartment in Seoul from January 2006 to June 2013, empirically compared and analyzed the estimation result of apartment price using OLS by hedonic price model for the problem of space-time correlation, temporal autoregressive model (TAR) considering temporal effect, spatial autoregressive model (SAR) spatial effect and spatiotemporal autoregressive model (STAR) spatiotemporal effect. As a result, the adjusted R-square of STAR model was increased by 10% compared that of OLS model while the root mean squares error (RMSE) was decreased by 18%. Considering temporal and spatial effect, it is observed that the estimation of apartment price is more correct than the existing model. As the result of analyzing STAR model, the apartment price is affected as follows; area for apartment(-), years of apartment(-), dummy of low-rise(-), individual heating (-), city gas(-), dummy of reconstruction(+), stairs(+), size of complex(+). The results of other analysis method were the same. When estimating the price of real estate using STAR model, the government officials can improve policy efficiency and make reasonable investment based on the objective information by grasping trend of real estate market accurately.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.2B
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• pp.163-171
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• 2009

Classical linear models have been generally used to analyze and forecast hydrologic time series. However, there is growing evidence of nonlinear structure in natural phenomena and hydrologic time series associated with their patterns and fluctuations. Therefore, the classical linear techniques for time series analysis and forecasting may not be appropriate for nonlinear processes. In recent, the BDS (Brock-Dechert-Scheinkman) statistic instead of conventional techniques has been used for detecting nonlinearity of time series. The BDS statistic was derived from the statistical properties of the correlation integral which is used to analyze chaotic system and has been effectively used for distinguishing nonlinear structure in dynamic system from random structures. DVS (Deterministic Versus Stochastic) algorithm has been used for detecting chaos and stochastic systems and for forecasting of chaotic system. This study showed the DVS algorithm can be also used for detecting nonlinearity of the time series. In this study, the stochastic and hydrologic time series are analyzed to detect their nonlinearity. The linear and nonlinear stochastic time series generated from ARMA and TAR (Threshold Auto Regressive) models, a daily streamflow at St. Johns river near Cocoa, Florida, USA and Great Salt Lake Volume (GSL) data, Utah, USA are analyzed, daily inflow series of Soyang dam and the results are compared. The results showed the BDS statistic is a powerful tool for distinguishing between linearity and nonlinearity of the time series and DVS plot can be also effectively used for distinguishing the nonlinearity of the time series.

• Journal of the Korean Society for Railway
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• v.15 no.2
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• pp.205-215
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• 2012

The purpose of this research is to identify the factors affecting the intention to adopt a transcontinental railway in Korea. We develop an empirically testable model that demonstrates the effects of factors including cost, service, and efficiency of railway transportation, on modal shift intention to railway, attitude of a Railway, and intention to adopt a Transcontinental Railway (KTAR) as a railway transportation mode in the end. A survey method enables us to analyze the model with a structural equation modeling. The empirical analysis reveals that two most influential factors-the modal shift to railway transportation and the attitude of a Railway-play roles in determining intention to adopt the Transcontinental Railway (KTAR). Of the factors of transportation mode, transportation cost has a greater impact than transportation service and transportation efficiency on the intention to adopt a Transcontinental Railway (KTAR).